Grist28%

The secret to a better grid? Electric vehicles. 25%

By Matt Simon44%

7/23/2026, 1:00:00 PM

BS Summary: This article contains 22 faulty reasoning types, including Appeal to Authority, Overconfidence Bias, and Quote-first Misdirection, with Optimism Bias as the most egregious example at 21.7% saturation with 208 hits. Analysis detected 1,071 faulty-reasoning hits from 957 analyzed words, generating a BS Score of 37% and a BS Rank of 25% (16,592 of 21,887 articles). This article is better (less manipulative) than 75.80% of the article peer group.

You can’t tell when you’re passing one on the highway, but an electric vehicle may well have a superpower. 
It charges by plugging into the electric grid, of course, but it might also be able to send energy back into it. 
For a growing number of EVs, this vehicle-to-grid technology, or V2G, creates a revenue stream for drivers, who utilities pay to tap into their batteries when demand on the grid spikes. 
Utilities across the country are pursuing pilot projects for the tech, figuring out how to coordinate hundreds, thousands, and eventually millions of EVs. 
To that end, today a coalition of companies  Eversource, National Grid, EnergyHub, Sunrun, and the Mobility House  is launching an early test of the technology in Massachusetts so utility customers can give it a try. 
Lessons learned here and elsewhere could drive the technique into the mainstream, making the grid more reliable, and electricity cheaper, even if you don’t own an EV. 
“It’s great to have Massachusetts stepping into the lead here and doing this because these learnings are what’s going to allow this technology to scale,” said Chip Silverman, director of grid services at Sunrun, a solar and battery company. 
In the new system, participants hook into an existing program called ConnectedSolutions, which allows homes to run off their residential batteries, among other things. 
Then when there’s a “demand response” event, like during a heat wave, EV batteries can help the grid keep up. 
Participants are compensated for this, just like some homeowners who provide energy from their solar panels. 
“It’s really kind of a small number of hours per year that you’re discharging the battery,” said Russell Vare, vice president of vehicle-grid integration at the Mobility House North America, a provider of charging infrastructure. 
“It’s not necessarily like a daily discharge. 
It’s just during those peak times the events are called.” 
Utilities like V2G because they’re dealing with escalating, overlapping challenges. 
For one, the demand for electricity is growing as more power-hungry data centers come online and people switch from internal combustion cars to EVs and from gas furnaces to heat pumps. 
At the same time, utilities are trying to ditch gas and coal in favor of renewables like wind and solar. 
These clean technologies, though, are intermittent, in that the wind isn’t always blowing and the sun isn’t always shining. 
Utilities need ways to bank energy for later use, which is why they’re building storage facilities and even using the Earth itself as a giant battery. 
Except some of that spending may indeed be avoidable: The promise of V2G is that it can make electricity cheaper. 
While participants need a bidirectional charger to send energy back to the grid, a utility doesn’t need to reinvent the system as a whole. 
EV batteries are an existing, widespread, and reliable source of backup energy to tap into in times of high demand, like during the summer when everyone is running their air conditioning. 
“It’s the cheapest cost of flexible energy storage that will be available for the grid,” Vare said. 
The hotter the planet gets, the more enticing V2G looks for utilities. 
People need additional AC to stay healthy, but the appliances require lots of power to run. 
If that energy isn’t coming from renewables, it’s causing even more warming and increasing demand for AC, and on and on. 
In a V2G system, vehicles that follow predictable schedules, like school buses and municipal fleets, will be especially useful, in addition to their batteries being enormous stores of energy. 
Even a typical EV battery, though, has around six times the capacity as a backup unit mounted outside a house. 
While not all EVs have the hardware needed to tap into V2G, more models are, like the Nissan Leaf, coming equipped to do so. 
And as with any technology, bidirectional chargers will get cheaper over time. 
“As hardware costs come down, installation becomes simpler, and standards continue to mature, we expect vehicle-to-grid to become dramatically more accessible over the next several years," said Seth Frader-Thompson, president of EnergyHub, in a statement. 
With EVs sitting idle all across a city, that adds up to some serious power. 
So much so, in fact, that only a fraction of owners would need to participate for a program to adequately support the grid. 
But the more people who opt in, the better, as that gives a utility a broader base to draw from. 
“If you have a higher number of batteries out there in a virtual power plant, you can actually use less energy from each individual battery,” Silverman said. 
“But collectively, when you patch them all together and aggregate them, it comes out to a very large resource. 
And that’s really where the magic is.” 
These early projects are figuring out how best to coordinate this, like with apps that let people specify when they typically use their vehicle to, say, get to work. 
(Participants in the new Massachusetts program are able to do this.) 
The overall idea is for EVs to send power back to the grid when demand is highest, like when people return home from work and switch on appliances. 
Then, as the night goes on, the vehicles can charge. 
This would be paired with another technique, known as active managed charging, which staggers when EVs juice up through the evening and early morning hours  that is, they’re not all doing so at 10 p.m., which would suddenly and dramatically increase demand on the grid. 
All told, V2G promises to turn consumers of electricity into more active participants in the grid, with power flowing both ways. 
Far from straining the grid to the point of collapse, EVs will instead help save it. 
Article reasoning-pattern comparisonThis article: 6.4%Matt Simon: 2.9%Grist: 2.2%Confirmation Bias6.4%This article: 1.3%Matt Simon: 0.5%Grist: 0.8%Anchoring Bias1.3%This article: 4.8%Matt Simon: 2.8%Grist: 3.0%Availability Heuristic4.8%This article: 6.3%Matt Simon: 0.8%Grist: 1.0%Representativeness Heuristic6.3%This article: 0.0%Matt Simon: 0.0%Grist: 0.5%Hindsight Bias0.0%This article: 9.9%Matt Simon: 4.7%Grist: 1.3%Overconfidence Bias9.9%This article: 3.9%Matt Simon: 5.6%Grist: 5.0%Framing Effect3.9%This article: 0.0%Matt Simon: 0.5%Grist: 0.7%Loss Aversion0.0%This article: 0.0%Matt Simon: 0.9%Grist: 0.5%Status Quo Bias0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.3%Sunk Cost Effect0.0%This article: 21.7%Matt Simon: 11.3%Grist: 3.1%Optimism Bias21.7%This article: 1.3%Matt Simon: 0.6%Grist: 2.0%Pessimism Bias1.3%This article: 1.7%Matt Simon: 2.2%Grist: 6.8%Negativity Bias1.7%This article: 2.1%Matt Simon: 1.9%Grist: 1.0%Self-Serving Bias2.1%This article: 0.0%Matt Simon: 0.6%Grist: 0.6%Fundamental Attribution Error0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Actor-Observer Bias0.0%This article: 0.0%Matt Simon: 0.2%Grist: 0.8%In-Group Bias0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.2%Out-Group Homogeneity Bias0.0%This article: 5.2%Matt Simon: 2.8%Grist: 1.0%Halo Effect5.2%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%Horn Effect0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Matt Simon: 1.1%Grist: 1.2%Recency Bias0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.3%Primacy Effect0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Blind-Spot Bias0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.3%Ad Hominem0.0%This article: 0.0%Matt Simon: 0.3%Grist: 0.1%Straw Man0.0%This article: 16.0%Matt Simon: 7.3%Grist: 4.1%Appeal to Authority16.0%This article: 1.7%Matt Simon: 2.8%Grist: 1.4%False Dilemma1.7%This article: 0.0%Matt Simon: 1.0%Grist: 0.9%Slippery Slope0.0%This article: 0.0%Matt Simon: 0.5%Grist: 0.1%Circular Reasoning0.0%This article: 0.0%Matt Simon: 7.2%Grist: 3.9%Hasty Generalization0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Red Herring0.0%This article: 2.1%Matt Simon: 1.9%Grist: 0.6%Bandwagon2.1%This article: 0.7%Matt Simon: 3.6%Grist: 4.0%Appeal to Emotion0.7%This article: 2.1%Matt Simon: 0.9%Grist: 0.7%Begging the Question2.1%This article: 5.0%Matt Simon: 3.1%Grist: 3.1%Post Hoc (False Cause)5.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%Tu Quoque0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.3%Burden of Proof0.0%This article: 0.0%Matt Simon: 0.4%Grist: 0.3%Appeal to Nature0.0%This article: 1.6%Matt Simon: 1.1%Grist: 0.3%Composition/Division1.6%This article: 2.0%Matt Simon: 0.6%Grist: 2.0%Anecdotal2.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%No True Scotsman0.0%This article: 0.0%Matt Simon: 2.4%Grist: 1.7%Ambiguity (Equivocation)0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Middle Ground0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Personal Incredulity0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Special Pleading0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.0%Genetic Fallacy0.0%This article: 0.0%Matt Simon: 1.1%Grist: 0.8%Unattributed Quote0.0%This article: 7.7%Matt Simon: 0.9%Grist: 1.0%Quote-first Misdirection7.7%This article: 4.9%Matt Simon: 6.4%Grist: 2.5%Biased Writer Voice4.9%This article: 0.0%Matt Simon: 2.7%Grist: 1.4%Indoctrination0.0%This article: 0.0%Matt Simon: 0.4%Grist: 1.0%Politically Left Leaning Bias0.0%This article: 0.0%Matt Simon: 0.0%Grist: 0.1%Politically Right Leaning Bias0.0%This article: 3.7%Matt Simon: 1.9%Grist: 0.7%Attempt to Sell a Product or S…3.7%

957 words analyzed.

Speakers

3speakers20%attributed speech761writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 6 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 31 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageChip Silverman • 39 words • 100.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageRussell Vare • 35 words • 100.0% coverageRussell Vare • 7 words • 0.0% coverageRussell Vare • 10 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageRussell Vare • 17 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageSeth Frader-Thompson • 35 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageChip Silverman • 27 words • 0.0% coverageChip Silverman • 19 words • 0.0% coverageChip Silverman • 7 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 46 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverage
Selected voice

Seth Frader-Thompson

100%flagged-word coverage
35 attributed words18% of attributed speech60% writer coverage
0%50.0%100.0%Quote-first Misdirection+100.0 ptsWriter: 0.0%Seth Frader-Thompson: 100.0%100.0%Biased Writer Voice-6.2 ptsWriter: 6.2%Seth Frader-Thompson: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.